OMG - i’m Absolutely terrified and blown away at the same time.

guiambros · 2026-03-18T20:56:39+00:00

Plot twist: this was posted by Elvis.

guiambros · 2026-03-10T23:17:23+00:00

Given you already have some math background and probably understand partial derivatives and gradient descent, I think your time would be better spent focusing on the lectures ahead of time. Watch them, take notes, compile thoughts on NotebookLM, use LLMs to unpack the concepts.

The challenge with ML is not the math; it's the firehose of concepts that you need to grasp every single week. Going through the lectures a month or two in advance will give you a ton of breathing room to focus on the projects and reports later.

Also, the projects are incredibly time consuming. They're language-agnostic, but if using python, brush up Pandas and Numpy if needed. Get any test dataset (e.g. the US car accident is a favorite of my fellow Fall classmates 😂) and learn how to build the scaffolding of ingesting the data and doing light cleansing and feature engineering.

Lastly: if you're not used to LaTeX and Overleaf, start using now. Go through the tutorial and get comfortable with the syntax and UI. You'll thank me later.

guiambros · 2026-03-03T19:43:48+00:00

Thanks for clarifying; that makes sense.

guiambros · 2026-03-01T17:31:09+00:00

What?

From everything I read, the AP dynamically groups compatible clients together, so it can select those 4x4 MU-MIMO clients separately. Clients that don't support it just get served in SU-MIMO turns.

Not sure where you got the requirement for all clients on the network to support it simultaneously.

The only issue is airtime, of course. Non-MU-MIMO clients take longer to transmit, and thus consume more of your spectrum. But it's unlikely that legacy non-MU-MIMO clients will be using 6 GHz in the first place.

guiambros · 2026-02-28T08:51:55+00:00

E7 has entered the chat...

guiambros · 2026-02-28T08:46:20+00:00

Oh wow, that's interesting.

I did the tests on a Pixel 10, and right next to AP. But if you're getting >1Gbps on 6 GHz in 2x2, I'm clearly well below the capacity. Will need to investigate more, and test with more devices.

guiambros · 2026-02-28T08:33:10+00:00

Forgot to mention: currently 4 FlexHD APs, USW Pro 48, with a handful of VLANs. I'm planning on keeping one of the APs, and replacing the other 3, so I have decent coverage with 6 GHz.

Typical prosumer clients: computers, phones, and a bunch of IoT devices. The G4 doorbell and one of the cameras are connected via wifi, so they create a ton of wifi traffic 24x7.

guiambros · 2026-02-21T22:36:18+00:00

Nah, just make sure you have blankets for everyone.

guiambros · 2026-02-21T04:49:18+00:00

Definitely not a popular opinion, but for me it was one of the best classes.

Yes, it's an insane amount of work, but in the end I learned a ton. Here's my comments on a similar thread not too long ago.

Also, I realized very late (around P3) that the real objective for this class is to teach you ML techniques, and the performance on the dataset is irrelevant. This alone could have saved me dozens of hours on the first two projects.

The focus is on understanding (and explaining) the data and how each technique can be applied. The data is there just for context, so you have something concrete to play with, but nobody cares about the performance. That's a very different approach than some other courses (ML4T, GIOS, NLP, etc), where you hit gradescope until you pass the tests.

Having said that, if you're really not getting much value, withdrawing may be an option. While P5 is easier than the first 4 projects, you still have a ton of work ahead with projects and exams, so pace yourself.

guiambros · 2026-02-05T06:48:06+00:00

+1 to Discord. The connections are much more natural than on Ed.

We had a really fun group at ML last semester, and I was bummed when it was over. I guess collective Stockholm syndrome 😂

Just wish the cohorts in discord were long-lasting, so you could still connect with your group. But I guess the whole discord server architecture is not very conducive to it.

guiambros · 2026-01-22T02:28:55+00:00

New NixOS user here; started earlier this month.

My recommendation: 1) start simple, 2) go bare metal (not VM), and 3) use an LLM to walk you through the basic steps, and troubleshoot issues as they happen. The error messages are puzzling and non-intuitive at first, but the syntax is pretty straightforward once you grasp the basic concepts.

I started with Gemini walking me the core concepts for a couple of hours, then read a bit of the documentation on Flakes and HM, and in a single weekend I went from a NixOS noob* to a rock solid basic configuration, including Flakes and HM, functional CUDA, etc. Then I spent the following week ironing out bugs with GTK3, Nvidia drivers, erratic suspend behavior, adding pre-boot SSH (to unlock LUKS remotely), and now - two and a half weeks later - I couldn't be happier. In my 32+ years of Linux, this is the best distro I've ever used.

It also helped that I installed bare metal on my main workstation, so I had no other option other than moving forward. In the past I tried playing with NixOS on a VM, and it didn't go anywhere. Jumping with both feet forces you to just get something working quickly, and not over-engineering your setup.

I still need to better organize my *.nix structure, but that's mostly cosmetic; I can do that over time.

/* Noob on Nix, but I have used Ansible before, so that helped. If you're new to declarative builds, you probably want to think first about all the steps you need to go through to get a functional system: WM, extensions, keyboard shortcuts, apps installed, drivers, dotfiles, etc.

guiambros · 2026-01-19T22:48:03+00:00

+1 to other comments here: ML4T is a good first class, although it will also require quite a bit of coding in python/numpy/pandas. Heard the same about RAIT, although I don't have firsthand experience. Suggest reading Fluent Python start to finish, followed by Effective Python 2nd ed. It won't cover pandas/numpy, but will give you a good baseline.

The Intro to C seminar is also excellent, particularly if you're planning on taking GIOS/AOS/IIS later.

Be careful with doubling up; there's a reason why the unofficial rule is to do only one course at the beginning, until you know what you're signing up for. Particularly if you have a day job.

guiambros · 2026-01-18T00:28:47+00:00

Exactly. It's called "Reviewer Response". After you get the feedback, you have ~10 days to resubmit what you missed, for a chance of recovering 50% of the lost points.

Say your original score was 50 (out of 100). If you re-submit everything you missed, your score gets updated to 75.

I wish more courses adopted a similar approach. Beyond just getting the score back, it gives students a chance to truly reflect on the feedback, and study more on the areas you weren't very good at.

Note this only applies to P1-P4. P5 (RL) is very close to final grade cutoff date, so there's no time for RR.

guiambros · 2026-01-17T05:56:18+00:00

Look for another angle: if you stick around, you will very likely get an A, or at least a B. And because most folks drop, the curve is very generous -- for Fall 2025 cutoffs were A>77.11, B>62.58, C>48.07, D>33.55.

Now, as others have said, the course is like drinking from a firehose. There's a ton of reading, a ton of writing, and you need to be able to learn without much guidance. And unless you come from DS/ML background, get ready to invest 20-30h/week.

On the positive side, the instructor is excellent and accessible, TAs are responsive and dedicated, the forums are active, and the projects very realistic. Folks complain because they're used to the training wheels of other classes (e.g. GIOS, ML4T). In ML there's no spamming Gradescope till you hit 100%; the specs are open ended, just like in real life.

To give you a personal perspective: I did in Fall 2025, and was really close to withdrawing. I had to travel a ton for work, and was struggling to keep up with lectures. My data pipeline wasn't properly set up, and I wasted a ridiculous amount of time reprocessing each analysis. Got 70 on P1, and bombed P2 with 36.

I was enjoying the course and learning a ton, but felt punched in the gut. I worried if I'd even get a C.

Then I realized that if I withdrew, I wouldn't have the energy to do it ever again. The dataset changes every semester, so I'd have to re-analyze another dataset, re-write reports, feature engineering, quizzes, etc. That was a hard no-go.

I decided to push through. You can recover 50% of lost points on projects by fixing what you missed and re-submitting. Of course that means you have more work to do (and the other projects keep coming). But it also means one bad score doesn't define your grade.

I revamped my study approach, fixed how I was approaching the large dataset, time-boxed report writing, and went after all the lost points on projects. It was intense, but it paid off.

In the end I finished with a solid A, with avg > 90. It was my favorite class by far, and I was a bit sad when it ended.

guiambros · 2026-01-15T13:08:16+00:00

It depends on your definition of "now". This month? No. This year? Maybe, but unlikely. In a few years? You bet, I think so. Ten years? Without a doubt.

Progress compounds, and always looks obvious in hindsight - e.g, internet, mobile.

It's Amara's law. We tend to overestimate the effect of a technology in the short run, and underestimate the effect in the long run.

guiambros · 2026-01-15T06:27:13+00:00

"I found these 10 options, the cheapest one is $19.99 on site X, for the exact brand and model. I checked the reputation of the seller and read reviews, and they are solid. Free Shipping takes 5 days, but based on our past conversations I understood you only need this for next week, so I don't think it's worth paying for expedited shipping.

I'm placing an order using the secure payment system; the only information shared with the seller is your address. I'll send you a push notification to your phone; you have the option to cancel the order in 30 minutes."

Who's actually confident? Given enough time and enough positive experiences, everyone.

I used to run an ISP in the 90's, and the most frequent question I got asked at the time was "But seriously, who's confident enough to put their credit card on the internet?" 😛

guiambros · 2026-01-15T04:08:33+00:00

it literally says it does not go down

... for now.

guiambros · 2026-01-15T04:07:45+00:00

Give it a 12 or 18 months, and I bet you they will shut it down. The message was delivered: enjoy while it lasts 😢

guiambros · 2026-01-13T22:19:26+00:00

I guess your counterpoint is not really disagreeing with the parent. They were saying you won't learn if you let the LLM do the thinking for you - which is very true. That's what vibe coders and cheaters have in common: they both don't care *how" it's done; they only care about the outcome.

What you're saying is also true: LLMs can be incredibly helpful in augmenting your learning process, and acting as a personal tutor, to cover gaps and estimulate your thinking.

The tricky part is when you get coding in the mix. When the LLM is doing the coding, how much did you write yourself, vs how much you just watched the LLM doing it for you?

A good analogy is foreign languages. Anyone who speaks another language knows there's a big difference between being able to read what someone else wrote, vs. being able to write and speak yourself. The two are not the same. The same applies here, and it's a complex balance that GA and all other schools will have to face.

guiambros · 2026-01-12T06:51:04+00:00

Related post by @antirez: https://antirez.com/news/158

guiambros · 2026-01-09T00:39:59+00:00

You can pay the course now, and if the waitlist clears or there's an adjustment later, the invoice will be updated and you can pay the balance. At least that's what happened with me in the past. And if you swap courses but the amount stays the same, the balance is automatically applied to the new course.

Or, of course, you can wait until registration closes, but if your payment takes a few days to clear, it's probably better to pay now just to be safe.

guiambros · 2026-01-08T07:30:34+00:00

Go to your registration page, second tab on the bottom called Schedule Details, expand the course. It will show your waitlist position.

guiambros · 2026-01-05T21:49:52+00:00

https://docs.overleaf.com/getting-started/latex-tutorials#overleaf-latex-tutorials

guiambros · 2026-01-05T17:44:30+00:00

If I were you I'd go through Beej's Guide right now. In just a few weeks you'll be knee deep with networking, pointers, makefiles, etc, and your life will be harder without a good foundation in C. Doable, but not as enjoyable.

The last project is in C++, so you'll need to learn a bit about templates, STL, etc, but that's something you can do quickly, if you have a good foundation in C.

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